---
title: "Exploratory Analysis of Daily EMA Data"
output: 
  flexdashboard::flex_dashboard:
    orientation: rows
    vertical_layout: scroll
    source: embed
---

```{r setup, include=FALSE}
# Setup options
knitr::opts_chunk$set(collapse = TRUE, comment = "#>")

# CRAN packages
library(flexdashboard)
library(dplyr)
library(knitr)
library(ggplot2)

# devtools::install_github("mbcann01/dataclean")
library(dataclean)

# Load data
load("/Users/bradcannell/Dropbox/Research/mChat/data/daily_april_2016.RData")

# Sort by case number and date
daily <- dplyr::arrange(daily, case_number, date)
```

Overview {.sidebar}
===============================================================================

Here we plot the aggregate unconditional distribution of responses for each of the following variables:

1. Feelings at time of assessment

2. Location at time of assessment

3. Activity at time of assessment

4. Physical activity yesterday

5. Diet yesterday

6. Medication use yesterday

7. Freetime activities yesterday

8. Meaningful Interaction yesterday

9. Substance use yesterday




Feeling
===============================================================================

Feelings Table
-------------------------------------------------------------------------------

### Feelings at time of assessment

```{r feeling_table}
x <- select(daily, happy, frustrated, sad, worried, restless, excited, calm, lonely, bored, sluggish)

vars = tools::toTitleCase(names(x)) # Title case labels

df <- data.frame(
  x1 = vars,
  x2 = NA,
  x3 = NA,
  x4 = NA,
  x5 = NA,
  x6 = NA,
  stringsAsFactors = FALSE
)

i <- 1
for (var in x) {
  resp_table <- table(var)
  resp <- as.vector(resp_table)
  df$x2[i] <- resp[1]
  df$x3[i] <- resp[2]
  df$x4[i] <- resp[3]
  df$x5[i] <- resp[4]
  df$x6[i] <- resp[5]
  i <- i + 1
}

names(df) <- c("Feeling", "Strongly Disagree", "Disagree", "Neutral", "Agree", "Strongly Agree")

kable(df)
```

Feelings Charts
-------------------------------------------------------------------------------

```{r plot_emotions}
for (var in vars) {
  plot <- ggplot(daily, aes_string(x = tolower(var))) +
    geom_bar() +
    scale_x_discrete("") +
    ggtitle(paste("I Feel", var, "Right Now")) +
    theme_bw()
  print(plot)
}
```




Location
===============================================================================

Location Table
-------------------------------------------------------------------------------

### Location at time of assessment

```{r location_table}
x <- select(daily, bus_loc, church_loc, home_loc, frifam_loc, store_loc, outdoors_loc, other_loc, restaurant_loc, school_loc, work_loc)

loc <- c("Bus, Train, or Vehicle", "Church", "Home", "Friend's or Relative's House", "Store / Mall", "Outdoors", "Other", "Restaurant", "School / Library", "Work")

df <- data.frame(
  x1 = loc,
  x2 = NA,
  x3 = NA,
  stringsAsFactors = FALSE
)

i <- 1
for (var in x) {
  resp_table <- table(var)
  resp <- as.vector(resp_table)
  df$x2[i] <- resp[1]
  df$x3[i] <- resp[2]
  i <- i + 1
}

names(df) <- c("Location", "No", "Yes")

kable(df)
```

Location Charts
-------------------------------------------------------------------------------

```{r plot_location}
x <- names(x)
i <- 1
for (var in x) {
  plot <- ggplot(daily, aes_string(x = var)) +
    geom_bar() +
    scale_x_discrete("") +
    ggtitle(paste("Location at Time of Assessment:", loc[i])) +
    theme_bw()
  print(plot)
  i <- i + 1
}
```




Activity
===============================================================================

Activity Table
-------------------------------------------------------------------------------

### Activity at time of assessment

```{r activity_table}
x <- select(daily, pre_who, sit_act, sleep_act, stand_act, talk_act, walk_act, other_act)

act <- c("Interacting With Someone", "Sitting", "Sleeping", "Standing", "Talking", "Walking / Excercising", "Other")

df <- data.frame(
  x1 = act,
  x2 = NA,
  x3 = NA,
  stringsAsFactors = FALSE
)

i <- 1
for (var in x) {
  resp_table <- table(var)
  resp <- as.vector(resp_table)
  df$x2[i] <- resp[1]
  df$x3[i] <- resp[2]
  i <- i + 1
}

names(df) <- c("Activity", "No", "Yes")

kable(df)
```

Activity Charts
-------------------------------------------------------------------------------

```{r plot_act}
x <- names(x)
i <- 1
for (var in x) {
  plot <- ggplot(daily, aes_string(x = var)) +
    geom_bar() +
    scale_x_discrete("") +
    ggtitle(paste(act[i], "Right Before the Phone Rang")) +
    theme_bw()
  print(plot)
  i <- i + 1
}
```




Physical Activity
===============================================================================

Table Row {.tabset .tabset-fade}
-------------------------------------------------------------------------------

### Physical activity yesterday (Yes / No)

```{r physact_table_1}
x <- select(daily, bike_yest, run_yest, cleaning_yest, none_yest, pedometer)

act <- c("Walked or Biked to Get Somewhere", "Engaged in Physical Fitness", "Engaged in Physical Activity at Work or Home", "Did None of These", "Used Pedometer")

df <- data.frame(
  x1 = act,
  x2 = NA,
  x3 = NA,
  stringsAsFactors = FALSE
)

i <- 1
for (var in x) {
  resp_table <- table(var)
  resp <- as.vector(resp_table)
  df$x2[i] <- resp[1]
  df$x3[i] <- resp[2]
  i <- i + 1
}

names(df) <- c("Activity", "No", "Yes")

kable(df)
```

### Physical activity yesterday (Minutes)

```{r physact_table_2}
x <- select(daily, min_walk, min_run, min_act)

act <- c("Walked or Biked to Get Somewhere", "Engaged in Physical Fitness", "Engaged in Physical Activity at Work or Home")

df <- data.frame(
  x1 = act,
  x2 = NA,
  x3 = NA,
  x4 = NA,
  x5 = NA,
  x6 = NA,
  x7 = NA,
  stringsAsFactors = FALSE
)

i <- 1
for (var in x) {
  resp_table <- table(var)
  resp <- as.vector(resp_table)
  df$x2[i] <- resp[1]
  df$x3[i] <- resp[2]
  df$x4[i] <- resp[3]
  df$x5[i] <- resp[4]
  df$x6[i] <- resp[5]
  df$x7[i] <- resp[6]
  i <- i + 1
}

names(df) <- c("Activity", "10 Minutes or Less", "11-20 Minutes", "21-30 Minutes", "31-40 Minutes", "41-50 Minutes", "More than 50 Minutes")

kable(df)
```

### Sitting time yesterday

```{r sitting_table}
df <- data.frame(
  x1 = NA,
  x2 = NA,
  x3 = NA,
  x4 = NA,
  x5 = NA,
  x6 = NA,
  stringsAsFactors = FALSE
)

resp_table <- table(daily$min_sit)
resp <- as.vector(resp_table)
df$x1 <- resp[1]
df$x2 <- resp[2]
df$x3 <- resp[3]
df$x4 <- resp[4]
df$x5 <- resp[5]
df$x6 <- resp[6]

names(df) <- c("4 or fewer hours", "More than 4 hours- 6 hours", "More than 6 hours- 8 hours", "More than 8 hours- 10 hours", "More than 10 hours - 12 hours", "More than 12 hours")

kable(df)
```

Physical Activity Charts
-------------------------------------------------------------------------------

```{r plot_act_yest}
x <- names(select(daily, bike_yest, run_yest, cleaning_yest, none_yest, pedometer, min_walk, min_run, min_act, min_sit))
act <- c("Walked or Biked to Get Somewhere", "Engaged in Physical Fitness", "Engaged in Physical Activity at Work or Home", "Did None of These", "Used Pedometer", "Walked or Biked to Get Somewhere", "Engaged in Physical Fitness", "Engaged in Physical Activity at Work or Home", "Sat")
i <- 1
for (var in x) {
  plot <- ggplot(daily, aes_string(x = var)) +
    geom_bar() +
    scale_x_discrete("") +
    ggtitle(paste(act[i], "Yesterday")) +
    theme_bw() +
    if (i > 5) {
      theme(axis.text.x = element_text(angle = 45, vjust = 0.5))
    } else {
      theme()
    }
  print(plot)
  i <- i + 1
}

# Plot steps
ggplot(daily, aes(x = steps)) +
  geom_histogram(binwidth = 1000) +
  scale_x_continuous("") +
  ggtitle("Steps Yesterday") +
  theme_bw()
```




Diet
===============================================================================

Table Row {.tabset .tabset-fade}
-------------------------------------------------------------------------------

### Ate any yesterday (Yes / No)

```{r diet_table_1}
x <- select(daily, any_fruit, any_veg, any_ssb, any_sweets, any_meat)

food <- c("Fruit", "Vegetables", "Sugar-Sweetened Beverages", "Deserts and Other Sweets", "Red Meat or Processed Meat")

df <- data.frame(
  x1 = food,
  x2 = NA,
  x3 = NA,
  stringsAsFactors = FALSE
)

i <- 1
for (var in x) {
  resp_table <- table(var)
  resp <- as.vector(resp_table)
  df$x2[i] <- resp[1]
  df$x3[i] <- resp[2]
  i <- i + 1
}

names(df) <- c("Food", "No", "Yes")

kable(df)
```

### Servings ate yesterday

```{r diet_table_2}
x <- select(daily, serv_fruit, serv_veg, serv_ssb, serv_sweets, serv_meat)

food <- c("Fruit", "Vegetables", "Sugar-Sweetened Beverages", "Deserts and Other Sweets", "Red Meat or Processed Meat")

df <- data.frame(
  x1 = food,
  x2 = NA,
  x3 = NA,
  x4 = NA,
  x5 = NA,
  x6 = NA,
  x7 = NA,
  stringsAsFactors = FALSE
)

i <- 1
for (var in x) {
  resp_table <- table(var)
  resp <- as.vector(resp_table)
  df$x2[i] <- resp[1]
  df$x3[i] <- resp[2]
  df$x4[i] <- resp[3]
  df$x5[i] <- resp[4]
  df$x6[i] <- resp[5]
  df$x7[i] <- resp[6]
  i <- i + 1
}

names(df) <- c("Food", "0 Servings", "1 Serving", "2 Servings", "3 Servings", "4 Servings", "5 or More Servings")

kable(df)
```

Diet Charts
-------------------------------------------------------------------------------

```{r diet_yest}
x <- names(select(daily, any_fruit, any_veg, any_ssb, any_sweets, any_meat, serv_fruit, serv_veg, serv_ssb, serv_sweets, serv_meat))

food <- c("Fruit", "Vegetables", "Sugar-Sweetened Beverages", "Deserts and Other Sweets", "Red Meat or Processed Meat", "Fruit", "Vegetables", "Sugar-Sweetened Beverages", "Deserts and Other Sweets", "Red Meat or Processed Meat")

i <- 1
for (var in x) {
  plot <- ggplot(daily, aes_string(x = var)) +
    geom_bar() +
    scale_x_discrete("") +
    ggtitle(paste("Ate", food[i], "Yesterday")) +
    theme_bw() +
    theme()
  print(plot)
  i <- i + 1
}
```




Medication
===============================================================================




Freetime
===============================================================================




Interaction
===============================================================================




Substances
===============================================================================

Substances Plot
-------------------------------------------------------------------------------

```{r plot_sub_yest}
x <- names(select(daily, alc_sub, cig_sub, mar_sub, opi_sub, stim_sub, herb_sub, other_sub, none_sub))
sub <- c("Alcohol", "Tobacco", "Marijuana", "Opiates", "Stimulants", "Herbal Drugs", "Another drug", "No Substances")
i <- 1
for (var in x) {
  plot <- ggplot(daily, aes_string(x = var)) +
    geom_bar() +
    scale_x_discrete("") +
    ggtitle(paste("Participant used", sub[i], "Yesterday")) +
    theme_bw()
  print(plot)
  i <- i + 1
}
```




Session Info
===============================================================================
```{r session_info, echo=FALSE}
sessionInfo()
```